Sparse separation: principles and tricks

Barak A. Pearlmutter; Vamsi K. Potluru

doi:10.1117/12.502473

1 April 2003 Sparse separation: principles and tricks

Barak A. Pearlmutter, Vamsi K. Potluru

Proceedings Volume 5102, Independent Component Analyses, Wavelets, and Neural Networks; (2003) https://doi.org/10.1117/12.502473
Event: AeroSense 2003, 2003, Orlando, Florida, United States

Abstract

Blind separation of linearly mixed white Gaussian sources is impossible, due to rotational symmetry. For this reason, all blind separation algorithms are based on some assumption concerning the fashion in which the situation departs from that insoluble case. Here we discuss the assumption of sparseness and try to put various algorithms that make the sparseness assumption in a common framework. The main objective of this paper is to give some rough intuitions, and to provide suitable hooks into the literature.

Citation Download Citation

Barak A. Pearlmutter and Vamsi K. Potluru "Sparse separation: principles and tricks", Proc. SPIE 5102, Independent Component Analyses, Wavelets, and Neural Networks, (1 April 2003); https://doi.org/10.1117/12.502473

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